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Optimal Investments Using Empirical Dynamic Programming with Application to Natural Resources

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  • Stensland, Gunnar
  • Tjostheim, Dag

Abstract

A number of problems arise when dynamic programming is applied to investment problems. Attempts have been made to circumvent these problems by using continuous time models where the state process is generated by a stochastic differential equation. In this article, the authors assume that the state process is described by a discrete Markov time-series model with empirically determined transition probabilities. Standard computer algorithms can then be used to obtain optimal policies. They apply their methods to two examples in natural resources, one of which has previously been analyzed by M. J. Brennan and E. S. Schwartz (1985) using continuous time models. The authors show that the optimal policies depend critically on the specification of the state process and, to a certain extent, on the discretization level used in the Markov approximation. Copyright 1989 by the University of Chicago.

Suggested Citation

  • Stensland, Gunnar & Tjostheim, Dag, 1989. "Optimal Investments Using Empirical Dynamic Programming with Application to Natural Resources," The Journal of Business, University of Chicago Press, vol. 62(1), pages 99-120, January.
    • Handle: RePEc:ucp:jnlbus:v:62:y:1989:i:1:p:99-120
    DOI: 10.1086/296453
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    Cited by:

    1. Lucija Muehlenbachs, 2015. "A Dynamic Model Of Cleanup: Estimating Sunk Costs In Oil And Gas Production," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(1), pages 155-185, February.
    2. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    3. Slade, Margaret E., 2001. "Valuing Managerial Flexibility: An Application of Real-Option Theory to Mining Investments," Journal of Environmental Economics and Management, Elsevier, vol. 41(2), pages 193-233, March.
    4. Muehlenbachs, Lucija, 2012. "Testing for Avoidance of Environmental Obligations," RFF Working Paper Series dp-12-12, Resources for the Future.

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